“Time is costly”:Modelling the macro-economic impact of scaling up access to antiretroviral treatment for HIV/AIDS

Jean-Paul Moatti*, Bruno Ventelou*, Yann Videau*, Michel Kazatchkine**

*INSERM Research Unit 379, University of the Mediterranean, Marseille**Ministry of Foreign Affairs, French Ambassador for HIV/AIDS  

ContextMacroeconomic policy constraints =- Control inflation- Avoid large-scale public deficit- Limit long term dependence on external donor financing- Opportunity costs of AIDS programmes for other poverty

reduction strategies

Limitations of available funding for reaching the

goal of universal access to HIV care & treatment in 2010

Three channels for impacting the economy Direct costs

AIDS treatment (including opportunistic diseases) reduction in savings lower accumulation of capital.

Indirect costs (short term)

AIDS invalidity reduction in labour participation.

Deferred indirect costs (long term)

AIDS Alteration of the long-term choices of the agents (households and firms) lower investment in physical & ‘human capital’ (education, knowledge, know-how)

Economic Impact of the HIV epidemic in developing countries

Previous macro-economic estimations of reduction in GNP attributable to

HIV/AIDS

Country

Average reduction in

GNP (in annual

growth points)

Period

Year

Sources/authors

30 sub-Saharan African

countries

0.8%- 1.4% 1990-2025 1992 Over (1992)

Cameroon 2% 1987-1991 1992 Kambou et alii (1992)

Zambia 1%-2% 1993-2000 1993 Forgy (1993) Tanzania 0.8% 1.4% 1991-2010 1991 Cuddington (1992)

Kenya 1.5% 1996-2005 1996 Hancock et alii (1996)

Mozambique 1% 1997-2020 2001 Wils et alii (2001)

Methods

Model of growth with multiple factors of accumulation (“endogenous” growth model: including choices on long term resources, as human capital)…

…Using the following macroeconomic production function:

with , population's epidemiological status and the constraint:

( ) ( ( , )) ( ( , ). ( , )) ( ( , ))Y K Y L Y H Y D Y

1

Methods Propriety of the model, two paths for the economy:

More production

AIDSIntensity of the crisis and/or weakness of the health policy response

More workers andmore productivity

More spendingin (human) capital

Less production

Less workers andless productivity

Less spendingin (human) capital

Above the epidemiological thresholdGrowth and development

Below the epidemiological thresholdTrap and involution

« Scaling up access to HIV treatment? »

“scaling up”? What we hypothesize:

"Scaling up HIV TRT"

0

0,2

0,4

0,6

0,8

1

1,2

2003 2004 2005 2006 2007 2008 2009 2010

a scenario of price

The policy response is represented through the following pathway: a reduction of the healthcare price index, which has the direct effect of increasing demand and consumption for healthcare…

‘‘Scaling up’’?

…Then (indirect effects), the model takes into account the fact that more healthy people can :

participate to the production with a greater likelihood

work better, now and in the future, as their (good) health status facilitates effort as well as transmission of knowledge and savoir-faire to others, including their own children.

“scaling up”? …How to read our results:

10 000

12 000

14 000

16 000

18 000

20 000

GDP GDP no aids GDP + Scaling-up HIV TRT

GDP if the AIDS-shock did

not occur

« Real » GDP(no scaling up)

If scaling up

Results

Results(i): success in five countries

Cameroon

1800019000200002100022000

23000240002500026000

Th

ou

san

ds

GDP

GDP no aids

GDP+scaling-up HIV TRT

Centre Afrique

34003600380040004200

4400460048005000

Th

ou

san

ds

GDP

GDP no aids

GDP+scaling-up HIV TRT

Benin

4800

5000

5200

5400

5600

5800

6000

Th

ou

san

ds

GDP

GDP no aids

GDP+scaling-upHIV TRT

Results(i): success in five countries

Scaling-up access to treatment would limit GDP losses due to AIDS from a 24.8% reduction in GDP loss in Central African Republic to a 85.2% in Angola, with Cameroon and Ivory Coast respectively presenting 32.9 and 32.1% reductions.

Angola

75008000850090009500

1000010500110001150012000

Th

ou

san

ds

GDP

GDP no aids

GDP+scaling-upHIV TRT

Ivory Coast

15000

16000

17000

18000

19000

20000

21000

Th

ou

san

ds

GDP

GDP no aids

GDP+scaling-up HIV TRT

Results (ii): failure in Zimbabwe

Zimbabwe does not seem to strongly react to scaling up with only a limited 10.3% reduction in GDP loss.

There is no range of the price policy which could redirect the country in the positive growth path (see the proprieties of an endogenous model of growth)

Zimbabwe

1900020000210002200023000

24000250002600027000

Th

ou

san

ds

GDP

GDP no aids

GDP+scaling-upHIV TRT

Results (iii): GDP-gains minus Costs

Table 2 shows that for four out of the six countries (Angola, Benin, Cameroon, Ivory Coast), the macroeconomic gains of scaling up would become potentially superior to its associated costs in 2010. At this date, these countries could de facto self-finance their program.

Net gains due to scaling up(thousand $)

2005 (f) 2010 (f)

Angola -178534 919677

Benin -107592 95475

Cameroon -649543 254001

Central African Republic -127989 -39708

Côte d’Ivoire -494694 47476

Zimbabwe -678767 -391701

Discussion

Discussion/limitations

Our simulations of the impact of scaling up treatment do not take into account how the increased availability of treatment may modify the dynamics of HIV transmission in the long run.

Ambiguity: mathematical epidemiologic models indicate the decreased infectiveness of treated patients is likely to be counterbalanced by the increase in life expectancy of the patients that will predictably translate into an increased probability of sexual encounters between sero-different partners…

Discussion/limitations

We introduced the policy of scaling up treatment by the way of a decrease in price of the health care commodities

In no way of course should it be considered as an evaluation of the impact of current programs. It is rather an attempt to simulate the potential economic gains that may be expected from scaling up to the extent that resources are used in an “ideally” efficient way (alongside the « healthcare demand function »)

Discussion/conclusion

A massive investment in scaling-up access to HIV treatment may efficiently counter-act the detrimental long term impact of the HIV pandemic for growth in Sub-Saharan Africa. Potential macroeconomic benefits of scaling up may even compensate for its associated costs at the 2010 horizon

Our approach also focuses attention on the importance of timing in the policy response. Delays may have irreversible effects. The policy response may be efficient in restoring the dynamics of growth, if and only if its implementation is carried out at a rapid and massive scale.